1. Field of the Invention
The invention relates to flow data reconciliation, the estimation of true flow values from measured flow values, and to the application of flow data reconciliation in process control.
2. Discussion of Related Art
Anytime sensors are used to measure flow in a chemical process, the resulting sensor measurements are susceptible to errors. Flow meters vary in their accuracy depending on the material in the stream, the conditions of the stream, and the sensing technology used in the sensor; and they vary in reproducibility as their performance deteriorates due to fouling, wear, or failure. Plants can improve or reduce sensor performance through frequency of maintenance. Thus, flow sensors have both fixed and variable performance factors.
Anytime that flow measurements are used for critical control or monitoring tasks in a chemical process, it is desirable to have the true flow value rather than the measured value, with its attendant uncertainty. This is especially true for two key uses of data: as input to process models and as input to closed loop control schemes. In these uses, inaccurate data can cause the generation of erroneous predictions or control moves, both of which could adversely affect performance of the process.
Although a process operator cannot have perfect knowledge of flow rates, there are techniques for deriving more accurate flow values. In many cases, all flows around a unit operation will be measured. Applying a fundamental engineering principle of mass conservation, a steady state material balance can be applied to a unit operation, which states that the flows in minus the flows out must equal zero.
When all the flows around a unit are measured, the measured flow values can be substituted into this material balance equation. However, due to inaccuracies in the measured flow values, the flows will not equate to zero. The difference between the actual sum and correct value of zero is the error (or residual) around the unit. Each measured flow value can then be adjusted to reduce the error in the balance equation to zero. The corrected flow values are estimates of the true flow values. Conventional techniques teach that for systems with random measurement errors it is preferred to adjust the flows by minimizing the sum of the squared differences between each measured and estimated flow value.
When a flow is unmeasured around a unit, there is not enough information to calculate the residual error, and thus no basis on which to estimate true flows. However, in some cases, the missing value is an output stream from one unit which is also an input stream to another unit. If a balance equation is written around both units, the flow value disappears from the balance. When the common flow value is the only missing flow for both units, a residual error can be calculated around the two units together, and thus new flow estimates can be made. The missing common flow value can then be estimated by completing the balances with the new flow estimates. Conventional techniques teach that this process can be expanded, making balances around all combinations of units. By this process it may be possible to make improved estimates for all flows in the process, even if insufficient flows are measured to make single-unit balances to correct all the flows.
In addition to the use of conservation of mass to develop balances around each unit, the art suggests that the principle of conservation of energy can also be applied. However, to compute energy flows around a unit, the enthalpy of each stream must be computed, plus direct energy flows (such as steam heating) must be estimated. In multicomponent streams, which are typical in chemical processes, stream enthalpy can only be computed if both the temperature and the composition of the stream are known. Since composition information is usually known for only some components in some streams and temperatures may be missing, this method is not generally useful in commercial practice.
Some conventional techniques teach that steady state balances be constructed for computing the errors. This means, however, that the technique cannot be applied to a process in which flows or inventories are changing. Since many process have dynamic flows or inventories, these techniques fail to address many important process situations.
Morover, some conventional technqiques teach that each error derives from the magnitude of the corrected versus measured value. This approach has the limitation that absolute errors in large flows tend to cause relatively large corrections to small flows.
Although in principle a complete set of reconciled flows could be obtained by conventional methods, a plant does not typically measure enough flows to build the balances around all the units in the plant. The absence of important flow measurement can severely limit the ability to derive corrected estimates.
To compensate for this, additional balances can be constructed by combining two or more units into a single material balance. This allows additional balances to be constructed, providing more opportunity to find balances in which all flows are measured. However, these techniques are very difficult to implement automatically. It requires a complicated search procedure to identify which multi-unit balances will improve the resulting estimates. It is thus very difficult to apply this technique where full sensor data is lacking. This approach is particularly difficult to implement in real world situations where analyzers both fail and are returned to service in a random manner across the process.
Furthermore, some conventional techniques teach summing the weighted squared errors of the corrected versus the raw flows, and minimizing the sum, where the weighs are selected based on prior knowledge of sensor performance and flow importance. However, this approach uses fixed weights, even though some flow sensors can and do undergo significant changes in accuracy. Thus a sensor whose behavior changes due to failure or deterioration could drive many related sensors to have incorrect adjusted estimates.
Other techniques teach a simple minimizing of the global error. However, there may be cases where the result of the process used to find the minimum error leads to corrections that are many times different than the expected corrections for one or more sensors. These techniques are incapable of detecting such problems.
Finally, some conventional techniques teach that stream compositions must be known to compute stream enthalpies. Since compositions are not generally known except for some components in some streams, conventional techniques are not practical for computing stream enthalpies.